This article is by Sonny Patel, Chief Product and Technology Officer at Socotra
AI is advancing rapidly in insurance, but trust has not kept pace. That gap reflects real technology constraints alongside the organizational work required to use AI responsibly. Because insurance is a high-stakes, highly regulated industry, trust is foundational. New systems need time, judgment, and discipline to earn confidence, and progress depends as much on human governance as on technical capability.
The Trust Gap Reflects Both Learning and Limits
AI agents perform well in narrow, clearly defined scenarios, but many insurance decisions resist simplification. Risk assessment depends on context. Claims decisions demand transparency and fairness. These are areas where current AI systems can assist but still struggle with nuance, data quality, and edge cases.
Skepticism often grows when AI systems operate without sufficient visibility. If business and technical leaders cannot see how conclusions were reached, what data informed them, or where authority stops, confidence erodes quickly. Trust does not come from sophistication alone; it comes from clarity about how a system behaves and where it may fall short.
Human Oversight Strengthens, Not Slows, AI
In insurance, human judgment is not a temporary safeguard but a permanent requirement. AI can accelerate analysis, surface insights, and propose actions, but accountability must remain with people. This is especially true in underwriting and claims, where outcomes must be explainable and defensible.
Well-designed systems make their reasoning visible and invite human intervention. When professionals can review, adjust, or override AI outputs, they improve decision quality while reinforcing trust. Over time, this interaction becomes a feedback loop that refines both the technology and the expertise around it.
Governance Turns Trust Into Practice
Responsible AI requires clear governance. AI agents should be treated like any mission-critical insurance system, with clear controls, defined permissions, and auditability. Governance frameworks help organizations manage real technical risks, from data exposure to unintended actions, while providing traceability for every decision an AI system supports.
This level of structure allows insurers to move faster without losing control. Trust becomes operational when systems are designed with accountability built in, rather than added after the fact.
Curiosity Is the Starting Point
Trust does not emerge automatically as technology improves. It grows through engagement. Insurers that actively test AI systems, question outputs, and study behavior across different contexts develop a more realistic understanding of what these tools can and cannot do.
That curiosity leads to shared norms around appropriate use, decision boundaries, and oversight. Over time, these norms become as important as technical progress in determining whether AI is trusted across the organization.
Trust as a Strategic Advantage
AI will not replace judgment in insurance, but it will change how judgment is exercised. Insurers that combine technical rigor with human oversight and thoughtful governance will be best positioned to scale AI responsibly. The future of AI in insurance will be shaped less by ambition and more by trust. The organizations that invest in building it deliberately will set the pace for the industry.
About Sonny Patel
Sonny Patel is the Chief Product and Technology Officer at Socotra, where she leads the Product and Engineering teams and owns and executes on Socotra’s product strategy. She is a recognized thought leader in AI with over 20 years of experience building and launching products at Fortune 500 companies. Prior to Socotra, Sonny was an integral leader at Dell, Microsoft, Amazon, and LivePerson. She holds an MBA in Strategy & Entrepreneurship from the Haas School of Business at the University of California, Berkeley and a Master’s in Computer Science from Texas A&M University.
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